Automatic Learning of Textual Entailments with Cross-Pair Similarities

In this paper we define a novel similarity measure between examples of textual entailments and we use it as a kernel function in Support Vector Machines (SVMs). This allows us to automatically learn the rewrite rules that describe a non trivial set of entailment cases. The experiments with the data sets of the RTE 2005 challenge show an improvement of 4.4% over the state-of-the-art methods.

• Type: Conference
• Year: 2006
• Where: ACL
• Authors: Fabio Massimo Zanzotto, Alessandro Moschitti
• Keywords: ACL 2006, ACL 2007, Non Trivial Set, RTE 2005 Challenge, Support Vector Machines